Alternative approaches to the widely known pignistic transformation of belief functions are presented and analyzed. A series of various probabilistic transformations is examined namely from the point of view of their consistency with rules for belief function combination and their consistency with probabilistic upper and lower bounds.A new definition of general probabilistic transformation is introduced and a discussion of their applicability is included.